The delivery of healthcare in the U.S. is increasingly based on healthcare teams, with an emphasis on coordination among providers from different disciplines. Poor team functioning is associated with poor patient care through adverse events, lack of coordination, and spiraling costs. In contrast, good team functioning is associated with improved patient outcomes, heightened staff satisfaction, and reduced burnout. Within VA, teams are being used in a variety of treatment settings including primary care (e.g. Patient Aligned Care Teams) and mental health outpatient services (e.g. Behavioral Health Interdisciplinary Program teams [BHIPs]). Unfortunately, many healthcare teams both within and outside of VA continue to perform poorly. What does it take to build an effective healthcare team? Numerous models suggest a set of common elements including leadership support, shared goals, and attention to communication. However, enhancing team functioning requires a significant time and resource investment?and time and resources are in short supply for many VA healthcare teams. Many studies have held up high-performing teams as examples of good teamwork?but such teams are frequently selected without regard for the baseline resources they have available. This raises the possibility that much of what we think we know about high-performing teams could be better labeled as ?what we know about well-resourced teams.? In such cases, the lessons learned may not be applicable to the lower-functioning, lower-resourced teams most in need of assistance. There is therefore an urgent need to develop concrete, actionable guidance for improving team outcomes for these teams. Research Objectives: In the context of VA outpatient general mental health (GMH) clinics, which are in the process of implementing BHIP-based team care, we aim to refine a process for identifying teams with good staff outcomes in the context of high workload-to-staffing ratios. We will also explore the teamwork processes and contextual factors that characterize these types of high-performing teams. This mixed-methods study will therefore lay the foundation for a follow-up IIR that aims to more comprehensively identify generalizable ways for teams to achieve good staff outcomes specifically in the context of high workload-to-staffing ratios. AIM 1: Classify VA outpatient GMH clinics as high versus low in staff outcomes (staff satisfaction, burnout, and turnover), and high versus low in workload-to-staffing ratios using existing VA data sources (the All- Employee Survey and Corporate Data Warehouse). We will contact VISN- and facility-level mental health leaders to identify outpatient BHIPs located within those clinics?two with high workload-to-staffing ratios and good staff outcomes; and two with low workload-to-staffing ratios and poor staff outcomes?in which to conduct qualitative interviews in Aim 2. AIM 2a: Use semi-structured qualitative interviews to validate our team selection process from Aim 1. Hypothesis 2a: We hypothesize that qualitative findings will suggest potential refinements to our team selection process undertaken in Aim 1 (specifically in terms of staff outcomes and workload-to-staffing ratios). AIM 2b: Based on the interviews from Aim 2a, we will identify teamwork and contextual factors that most strongly differentiate these two types of teams, consistent with a Positive Deviance approach. Analyses will be pursued by Directed Content Analysis, with additional attention given to emergent themes. Outpatient BHIPs embedded within the identified outpatient GMH clinics provide an ideal environment for this aim given their interdisciplinary, heterogeneous structure; their national mandate to work together as a team; and the commitment from the Office of Mental Health Operations to enhance staff outcomes via the BHIP initiative. Hypothesis 2b: We hypothesize that a number of teamwork elements (especially psychological safety and relational coordination) will differentiate BHIPs with good staff outcomes despite high workload-to-staffing ratios from teams with poor staff outcomes despite low workload-to-staffing ratios.